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<div class="title">segNet.h</div>  </div>
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<a href="segNet_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2017, NVIDIA CORPORATION. All rights reserved.</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> * copy of this software and associated documentation files (the &quot;Software&quot;),</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> * to deal in the Software without restriction, including without limitation</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> * the rights to use, copy, modify, merge, publish, distribute, sublicense,</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> * and/or sell copies of the Software, and to permit persons to whom the</span></div>
<div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> * Software is furnished to do so, subject to the following conditions:</span></div>
<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> * all copies or substantial portions of the Software.</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div>
<div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL</span></div>
<div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> * THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div>
<div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING</span></div>
<div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="comment"> * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER</span></div>
<div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment"> * DEALINGS IN THE SOFTWARE.</span></div>
<div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment"> */</span></div>
<div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160; </div>
<div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="preprocessor">#ifndef __SEGMENTATION_NET_H__</span></div>
<div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;<span class="preprocessor">#define __SEGMENTATION_NET_H__</span></div>
<div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160; </div>
<div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160; </div>
<div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="tensorNet_8h.html">tensorNet.h</a>&quot;</span></div>
<div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160; </div>
<div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160; </div>
<div class="line"><a name="l00034"></a><span class="lineno"><a class="line" href="group__segNet.html#ga33b5fd20f8ed468725c55eb0bcc5af71">   34</a></span>&#160;<span class="preprocessor">#define SEGNET_DEFAULT_INPUT   &quot;input_0&quot;</span></div>
<div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160; </div>
<div class="line"><a name="l00040"></a><span class="lineno"><a class="line" href="group__segNet.html#ga05c359c7dcd0c1e855543a3a9a18c422">   40</a></span>&#160;<span class="preprocessor">#define SEGNET_DEFAULT_OUTPUT  &quot;output_0&quot;</span></div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160; </div>
<div class="line"><a name="l00046"></a><span class="lineno"><a class="line" href="group__segNet.html#ga19f1910138ebb47efda640bf02f7caee">   46</a></span>&#160;<span class="preprocessor">#define SEGNET_DEFAULT_ALPHA 150</span></div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160; </div>
<div class="line"><a name="l00052"></a><span class="lineno"><a class="line" href="group__segNet.html#gad66854e2f925b6648b1d3f68335658e4">   52</a></span>&#160;<span class="preprocessor">#define SEGNET_MODEL_TYPE &quot;segmentation&quot;</span></div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160; </div>
<div class="line"><a name="l00058"></a><span class="lineno"><a class="line" href="group__segNet.html#ga1b784139a64e71b3698a234d83ae2cf8">   58</a></span>&#160;<span class="preprocessor">#define SEGNET_USAGE_STRING  &quot;segNet arguments: \n&quot;                                                     \</span></div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;<span class="preprocessor">                  &quot;  --network=NETWORK    pre-trained model to load, one of the following:\n&quot;   \</span></div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;<span class="preprocessor">                  &quot;                           * fcn-resnet18-cityscapes-512x256\n&quot;                      \</span></div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;<span class="preprocessor">                  &quot;                           * fcn-resnet18-cityscapes-1024x512\n&quot;                     \</span></div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;<span class="preprocessor">                  &quot;                           * fcn-resnet18-cityscapes-2048x1024\n&quot;                    \</span></div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;<span class="preprocessor">                  &quot;                           * fcn-resnet18-deepscene-576x320\n&quot;                       \</span></div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;<span class="preprocessor">                  &quot;                           * fcn-resnet18-deepscene-864x480\n&quot;                       \</span></div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;<span class="preprocessor">                  &quot;                           * fcn-resnet18-mhp-512x320\n&quot;                                     \</span></div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;<span class="preprocessor">                  &quot;                           * fcn-resnet18-mhp-640x360\n&quot;                                     \</span></div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;<span class="preprocessor">                  &quot;                           * fcn-resnet18-voc-320x320 (default)\n&quot;                   \</span></div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;<span class="preprocessor">                  &quot;                           * fcn-resnet18-voc-512x320\n&quot;                                     \</span></div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;<span class="preprocessor">                  &quot;                           * fcn-resnet18-sun-512x400\n&quot;                                     \</span></div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;<span class="preprocessor">                  &quot;                           * fcn-resnet18-sun-640x512\n&quot;                     \</span></div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;<span class="preprocessor">                  &quot;  --model=MODEL        path to custom model to load (caffemodel, uff, or onnx)\n&quot;                    \</span></div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;<span class="preprocessor">                  &quot;  --prototxt=PROTOTXT  path to custom prototxt to load (for .caffemodel only)\n&quot;                             \</span></div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;<span class="preprocessor">                  &quot;  --labels=LABELS      path to text file containing the labels for each class\n&quot;                             \</span></div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160;<span class="preprocessor">                  &quot;  --colors=COLORS      path to text file containing the colors for each class\n&quot;                             \</span></div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;<span class="preprocessor">                  &quot;  --input-blob=INPUT   name of the input layer (default: &#39;&quot; SEGNET_DEFAULT_INPUT &quot;&#39;)\n&quot;              \</span></div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;<span class="preprocessor">                  &quot;  --output-blob=OUTPUT name of the output layer (default: &#39;&quot; SEGNET_DEFAULT_OUTPUT &quot;&#39;)\n&quot;            \</span></div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;<span class="preprocessor">            &quot;  --alpha=ALPHA        overlay alpha blending value, range 0-255 (default: 150)\n&quot;                 \</span></div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;<span class="preprocessor">                  &quot;  --visualize=VISUAL   visualization flags (e.g. --visualize=overlay,mask)\n&quot;                                \</span></div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;<span class="preprocessor">                  &quot;                       valid combinations are:  &#39;overlay&#39;, &#39;mask&#39;\n&quot;                                         \</span></div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;<span class="preprocessor">                  &quot;  --profile            enable layer profiling in TensorRT\n\n&quot;</span></div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160; </div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160; </div>
<div class="line"><a name="l00087"></a><span class="lineno"><a class="line" href="group__segNet.html">   87</a></span>&#160;<span class="keyword">class </span><a class="code" href="group__segNet.html#classsegNet">segNet</a> : <span class="keyword">public</span> <a class="code" href="group__tensorNet.html#classtensorNet">tensorNet</a></div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;{</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160;<span class="keyword">public</span>:</div>
<div class="line"><a name="l00093"></a><span class="lineno"><a class="line" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0">   93</a></span>&#160;        <span class="keyword">enum</span> <a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a></div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;        {</div>
<div class="line"><a name="l00095"></a><span class="lineno"><a class="line" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0abe4ae38cf99cdab6c3b070ee4a83bb47">   95</a></span>&#160;                <a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0abe4ae38cf99cdab6c3b070ee4a83bb47">FILTER_POINT</a> = 0,       </div>
<div class="line"><a name="l00096"></a><span class="lineno"><a class="line" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">   96</a></span>&#160;                <a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">FILTER_LINEAR</a>           </div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160;        };</div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160; </div>
<div class="line"><a name="l00102"></a><span class="lineno"><a class="line" href="group__segNet.html#a09a07cb06cd461f6003b655e945d9cf3">  102</a></span>&#160;        <span class="keyword">enum</span> <a class="code" href="group__segNet.html#a09a07cb06cd461f6003b655e945d9cf3">VisualizationFlags</a></div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;        {</div>
<div class="line"><a name="l00104"></a><span class="lineno"><a class="line" href="group__segNet.html#a09a07cb06cd461f6003b655e945d9cf3ab6a2dc917492d6b83de4b94c9233cb5f">  104</a></span>&#160;                <a class="code" href="group__segNet.html#a09a07cb06cd461f6003b655e945d9cf3ab6a2dc917492d6b83de4b94c9233cb5f">VISUALIZE_OVERLAY</a> = (1 &lt;&lt; 0),  </div>
<div class="line"><a name="l00105"></a><span class="lineno"><a class="line" href="group__segNet.html#a09a07cb06cd461f6003b655e945d9cf3a44b13e054270ce1d9a77fea8bfa83bd5">  105</a></span>&#160;                <a class="code" href="group__segNet.html#a09a07cb06cd461f6003b655e945d9cf3a44b13e054270ce1d9a77fea8bfa83bd5">VISUALIZE_MASK</a>    = (1 &lt;&lt; 1),  </div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;        };</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160; </div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;        <span class="keyword">static</span> uint32_t <a class="code" href="group__segNet.html#af480f63626ccb573caa816c9446930f5">VisualizationFlagsFromStr</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* str, uint32_t default_value=<a class="code" href="group__segNet.html#a09a07cb06cd461f6003b655e945d9cf3ab6a2dc917492d6b83de4b94c9233cb5f">VISUALIZE_OVERLAY</a> );</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160; </div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a> <a class="code" href="group__segNet.html#a299e7f53cde4e3e25cd00829dc181a10">FilterModeFromStr</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* str, <a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a> default_value=<a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">FILTER_LINEAR</a> );</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160; </div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__segNet.html#classsegNet">segNet</a>* <a class="code" href="group__segNet.html#af5a935f07770a98dcd33d59d8e9751d1">Create</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* network=<span class="stringliteral">&quot;fcn-resnet18-voc&quot;</span>, uint32_t maxBatchSize=<a class="code" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>,</div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;                                           <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, <span class="keywordtype">bool</span> allowGPUFallback=<span class="keyword">true</span> );</div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;        </div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__segNet.html#classsegNet">segNet</a>* <a class="code" href="group__segNet.html#af5a935f07770a98dcd33d59d8e9751d1">Create</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* prototxt_path, <span class="keyword">const</span> <span class="keywordtype">char</span>* model_path, </div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;                                           <span class="keyword">const</span> <span class="keywordtype">char</span>* class_labels, <span class="keyword">const</span> <span class="keywordtype">char</span>* class_colors=NULL,</div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;                                           <span class="keyword">const</span> <span class="keywordtype">char</span>* input = <a class="code" href="group__segNet.html#ga33b5fd20f8ed468725c55eb0bcc5af71">SEGNET_DEFAULT_INPUT</a>, </div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;                                           <span class="keyword">const</span> <span class="keywordtype">char</span>* output = <a class="code" href="group__segNet.html#ga05c359c7dcd0c1e855543a3a9a18c422">SEGNET_DEFAULT_OUTPUT</a>,</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;                                           uint32_t maxBatchSize=<a class="code" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, </div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;                                           <a class="code" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="code" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, </div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;                                           <a class="code" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="code" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, <span class="keywordtype">bool</span> allowGPUFallback=<span class="keyword">true</span> );</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;        </div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160; </div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__segNet.html#classsegNet">segNet</a>* <a class="code" href="group__segNet.html#af5a935f07770a98dcd33d59d8e9751d1">Create</a>( <span class="keywordtype">int</span> argc, <span class="keywordtype">char</span>** argv );</div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;        </div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;        <span class="keyword">static</span> <a class="code" href="group__segNet.html#classsegNet">segNet</a>* <a class="code" href="group__segNet.html#af5a935f07770a98dcd33d59d8e9751d1">Create</a>( <span class="keyword">const</span> <a class="code" href="group__commandLine.html#classcommandLine">commandLine</a>&amp; cmdLine );</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;        </div>
<div class="line"><a name="l00160"></a><span class="lineno"><a class="line" href="group__segNet.html#a0e11d4bd854120f1709c306e91e44389">  160</a></span>&#160;        <span class="keyword">static</span> <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__segNet.html#a0e11d4bd854120f1709c306e91e44389">Usage</a>()               { <span class="keywordflow">return</span> <a class="code" href="group__segNet.html#ga1b784139a64e71b3698a234d83ae2cf8">SEGNET_USAGE_STRING</a>; }</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160; </div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;        <span class="keyword">virtual</span> <a class="code" href="group__segNet.html#a167f9d7e76b2837485278bf7323b4eac">~segNet</a>();</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160;        </div>
<div class="line"><a name="l00175"></a><span class="lineno"><a class="line" href="group__segNet.html#a04b332bd106de1f8238d34f36fb97442">  175</a></span>&#160;        <span class="keyword">template</span>&lt;<span class="keyword">typename</span> T&gt; <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#a04b332bd106de1f8238d34f36fb97442">Process</a>( T* input, uint32_t width, uint32_t height, <span class="keyword">const</span> <span class="keywordtype">char</span>* ignore_class=<span class="stringliteral">&quot;void&quot;</span> )         { <span class="keywordflow">return</span> <a class="code" href="group__segNet.html#a04b332bd106de1f8238d34f36fb97442">Process</a>((<span class="keywordtype">void</span>*)input, width, height, imageFormatFromType&lt;T&gt;(), ignore_class); }</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;        </div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#a04b332bd106de1f8238d34f36fb97442">Process</a>( <span class="keywordtype">void</span>* input, uint32_t width, uint32_t height, <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> format, <span class="keyword">const</span> <span class="keywordtype">char</span>* ignore_class=<span class="stringliteral">&quot;void&quot;</span> );</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160; </div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#a04b332bd106de1f8238d34f36fb97442">Process</a>( <span class="keywordtype">float</span>* input, uint32_t width, uint32_t height, <span class="keyword">const</span> <span class="keywordtype">char</span>* ignore_class=<span class="stringliteral">&quot;void&quot;</span> );</div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160; </div>
<div class="line"><a name="l00201"></a><span class="lineno"><a class="line" href="group__segNet.html#af7b6257716514631dd0358e4b2ed692c">  201</a></span>&#160;        <span class="keyword">template</span>&lt;<span class="keyword">typename</span> T&gt; <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#af7b6257716514631dd0358e4b2ed692c">Mask</a>( T* output, uint32_t width, uint32_t height, <a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a> filter=<a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">FILTER_LINEAR</a> )                           { <span class="keywordflow">return</span> <a class="code" href="group__segNet.html#af7b6257716514631dd0358e4b2ed692c">Mask</a>((<span class="keywordtype">void</span>*)output, width, height, imageFormatFromType&lt;T&gt;(), filter); }</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;        </div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#af7b6257716514631dd0358e4b2ed692c">Mask</a>( <span class="keywordtype">void</span>* output, uint32_t width, uint32_t height, <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> format, <a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a> filter=<a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">FILTER_LINEAR</a> );</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160; </div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#af7b6257716514631dd0358e4b2ed692c">Mask</a>( <span class="keywordtype">float</span>* output, uint32_t width, uint32_t height, <a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a> filter=<a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">FILTER_LINEAR</a> );</div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160; </div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#af7b6257716514631dd0358e4b2ed692c">Mask</a>( uint8_t* output, uint32_t width, uint32_t height );</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160; </div>
<div class="line"><a name="l00229"></a><span class="lineno"><a class="line" href="group__segNet.html#a646b59503f89809fefee1c32d33307d9">  229</a></span>&#160;        <span class="keyword">template</span>&lt;<span class="keyword">typename</span> T&gt; <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#a646b59503f89809fefee1c32d33307d9">Overlay</a>( T* output, uint32_t width, uint32_t height, <a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a> filter=<a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">FILTER_LINEAR</a> )                        { <span class="keywordflow">return</span> <a class="code" href="group__segNet.html#a646b59503f89809fefee1c32d33307d9">Overlay</a>((<span class="keywordtype">void</span>*)output, width, height, imageFormatFromType&lt;T&gt;(), filter); }</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;        </div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#a646b59503f89809fefee1c32d33307d9">Overlay</a>( <span class="keywordtype">void</span>* output, uint32_t width, uint32_t height, <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> format, <a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a> filter=<a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">FILTER_LINEAR</a> );</div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160; </div>
<div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#a646b59503f89809fefee1c32d33307d9">Overlay</a>( <span class="keywordtype">float</span>* output, uint32_t width, uint32_t height, <a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a> filter=<a class="code" href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">FILTER_LINEAR</a> );</div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160; </div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;        <span class="keywordtype">int</span> <a class="code" href="group__segNet.html#a04bb46f8a71a45044d324a5e140f0777">FindClassID</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* label_name );</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160; </div>
<div class="line"><a name="l00263"></a><span class="lineno"><a class="line" href="group__segNet.html#a31e8118b2a38e330b6e087cf6c98396e">  263</a></span>&#160;        <span class="keyword">inline</span> uint32_t <a class="code" href="group__segNet.html#a31e8118b2a38e330b6e087cf6c98396e">GetNumClasses</a>()<span class="keyword"> const                                           </span>{ <span class="keywordflow">return</span> <a class="code" href="tensorNet_8h.html#a2dd230b8ba7267356e52b308b5c40077">DIMS_C</a>(<a class="code" href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">mOutputs</a>[0].dims); }</div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160; </div>
<div class="line"><a name="l00268"></a><span class="lineno"><a class="line" href="group__segNet.html#a895252269f201c23e8887d2774ec5ac4">  268</a></span>&#160;        <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__segNet.html#a895252269f201c23e8887d2774ec5ac4">GetClassLabel</a>( uint32_t <span class="keywordtype">id</span> )<span class="keyword"> const                   </span>{ <span class="keywordflow">return</span> <a class="code" href="group__segNet.html#af35b6253e85cfe6c30ac0a1a7ca3fcc8">GetClassDesc</a>(<span class="keywordtype">id</span>); }</div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;        </div>
<div class="line"><a name="l00273"></a><span class="lineno"><a class="line" href="group__segNet.html#af35b6253e85cfe6c30ac0a1a7ca3fcc8">  273</a></span>&#160;        <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__segNet.html#af35b6253e85cfe6c30ac0a1a7ca3fcc8">GetClassDesc</a>( uint32_t <span class="keywordtype">id</span> )<span class="keyword"> const                    </span>{ <span class="keywordflow">return</span> <span class="keywordtype">id</span> &lt; <a class="code" href="group__segNet.html#a5763fca156e99d9fe07dcbf626489b0e">mClassLabels</a>.size() ? <a class="code" href="group__segNet.html#a5763fca156e99d9fe07dcbf626489b0e">mClassLabels</a>[id].c_str() : NULL; }</div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;        </div>
<div class="line"><a name="l00278"></a><span class="lineno"><a class="line" href="group__segNet.html#afdf19dd9b97d89fa0074c75db4263eac">  278</a></span>&#160;        <span class="keyword">inline</span> float4 <a class="code" href="group__segNet.html#afdf19dd9b97d89fa0074c75db4263eac">GetClassColor</a>( uint32_t <span class="keywordtype">id</span> )<span class="keyword"> const                                </span>{ <span class="keywordflow">return</span> <a class="code" href="group__segNet.html#a307dd9f1d322ce42f553361321bbb869">mClassColors</a>[id]; }</div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160; </div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;        <span class="keywordtype">void</span> <a class="code" href="group__segNet.html#ac93f4a93e1321260a8f0584614185305">SetClassColor</a>( uint32_t classIndex, <span class="keyword">const</span> float4&amp; <a class="code" href="cudaPointCloud_8h.html#a549d5369c70bd71a70798aa5b1ea4270">color</a> );</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;        </div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;        <span class="keywordtype">void</span> <a class="code" href="group__segNet.html#ac93f4a93e1321260a8f0584614185305">SetClassColor</a>( uint32_t classIndex, <span class="keywordtype">float</span> r, <span class="keywordtype">float</span> g, <span class="keywordtype">float</span> b, <span class="keywordtype">float</span> a=255.0f );</div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;        </div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;        <span class="keywordtype">float</span> <a class="code" href="group__segNet.html#a27a03d12169f62dac97e351b2acdea86">GetOverlayAlpha</a>() <span class="keyword">const</span>;</div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;        </div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;        <span class="keywordtype">void</span> <a class="code" href="group__segNet.html#aa4c64609fb07586bed32ac4b8e9058d7">SetOverlayAlpha</a>( <span class="keywordtype">float</span> <a class="code" href="cudaVector_8h.html#aa94774faf063d34dab6f3f374d73ea7a">alpha</a>, <span class="keywordtype">bool</span> explicit_exempt=<span class="keyword">true</span> );</div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160; </div>
<div class="line"><a name="l00304"></a><span class="lineno"><a class="line" href="group__segNet.html#a973c337a2c3d7371c6b7cebd3aa2ade0">  304</a></span>&#160;        <span class="keyword">inline</span> <span class="keyword">const</span> <span class="keywordtype">char</span>* <a class="code" href="group__segNet.html#a973c337a2c3d7371c6b7cebd3aa2ade0">GetClassPath</a>()<span class="keyword"> const                                         </span>{ <span class="keywordflow">return</span> <a class="code" href="group__segNet.html#af9a9bd73dc17940aa87aacba2001b09b">mClassPath</a>.c_str(); }</div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160; </div>
<div class="line"><a name="l00310"></a><span class="lineno"><a class="line" href="group__segNet.html#a96b6fe6b05534c0792f8cc9353723219">  310</a></span>&#160;        <span class="keyword">inline</span> uint32_t <a class="code" href="group__segNet.html#a96b6fe6b05534c0792f8cc9353723219">GetGridWidth</a>()<span class="keyword"> const                                            </span>{ <span class="keywordflow">return</span> <a class="code" href="tensorNet_8h.html#a7d959cb65990da8bfea3d941d6daf416">DIMS_W</a>(<a class="code" href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">mOutputs</a>[0].dims); }</div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160; </div>
<div class="line"><a name="l00316"></a><span class="lineno"><a class="line" href="group__segNet.html#a95980d825a9939d0f48bfb2ef51ebb79">  316</a></span>&#160;        <span class="keyword">inline</span> uint32_t <a class="code" href="group__segNet.html#a95980d825a9939d0f48bfb2ef51ebb79">GetGridHeight</a>()<span class="keyword"> const                                           </span>{ <span class="keywordflow">return</span> <a class="code" href="tensorNet_8h.html#a1fc0b1785ea99bd75ec83b1eeb4e6120">DIMS_H</a>(<a class="code" href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">mOutputs</a>[0].dims); }</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160; </div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;<span class="keyword">protected</span>:</div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;        <a class="code" href="group__segNet.html#af2a45b6307104ed74714349becc0495c">segNet</a>();</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;        </div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#a3b98b9827d5c07e84ed6711414b96554">classify</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* ignore_class );</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160; </div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#aeb2ea51dc7597c832bcb1ae61301d678">overlayPoint</a>( <span class="keywordtype">void</span>* input, uint32_t in_width, uint32_t in_height, <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> in_format, <span class="keywordtype">void</span>* output, uint32_t out_width, uint32_t out_height, <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> out_format, <span class="keywordtype">bool</span> mask_only );</div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#aadc91d5c05834ab706691c4861448bc8">overlayLinear</a>( <span class="keywordtype">void</span>* input, uint32_t in_width, uint32_t in_height, <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> in_format, <span class="keywordtype">void</span>* output, uint32_t out_width, uint32_t out_height, <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> out_format, <span class="keywordtype">bool</span> mask_only );</div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;        </div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#a218a2c71cb4d59476070385c7370f789">loadClassColors</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* filename );</div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#a31d2bd6ddf05ce178a8e6c5b88247075">loadClassLabels</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* filename );</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;        <span class="keywordtype">bool</span> <a class="code" href="group__segNet.html#a4eabed9f0e8aa5a8ddad078ada771ad7">saveClassLegend</a>( <span class="keyword">const</span> <span class="keywordtype">char</span>* filename );</div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160; </div>
<div class="line"><a name="l00330"></a><span class="lineno"><a class="line" href="group__segNet.html#a5763fca156e99d9fe07dcbf626489b0e">  330</a></span>&#160;        std::vector&lt;std::string&gt; <a class="code" href="group__segNet.html#a5763fca156e99d9fe07dcbf626489b0e">mClassLabels</a>;</div>
<div class="line"><a name="l00331"></a><span class="lineno"><a class="line" href="group__segNet.html#af9a9bd73dc17940aa87aacba2001b09b">  331</a></span>&#160;        std::string <a class="code" href="group__segNet.html#af9a9bd73dc17940aa87aacba2001b09b">mClassPath</a>;</div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160; </div>
<div class="line"><a name="l00333"></a><span class="lineno"><a class="line" href="group__segNet.html#ac8cbd9449fb81520a847aee04b6bbca5">  333</a></span>&#160;        <span class="keywordtype">bool</span>*    <a class="code" href="group__segNet.html#ac8cbd9449fb81520a847aee04b6bbca5">mColorsAlphaSet</a>;       </div>
<div class="line"><a name="l00334"></a><span class="lineno"><a class="line" href="group__segNet.html#a307dd9f1d322ce42f553361321bbb869">  334</a></span>&#160;        float4*  <a class="code" href="group__segNet.html#a307dd9f1d322ce42f553361321bbb869">mClassColors</a>;          </div>
<div class="line"><a name="l00335"></a><span class="lineno"><a class="line" href="group__segNet.html#a3db3738778929458b52a709b053d456a">  335</a></span>&#160;        uint8_t* <a class="code" href="group__segNet.html#a3db3738778929458b52a709b053d456a">mClassMap</a>;                     </div>
<div class="line"><a name="l00337"></a><span class="lineno"><a class="line" href="group__segNet.html#aadacbaf1eb15bfe512499276272bf67c">  337</a></span>&#160;        <span class="keywordtype">void</span>*     <a class="code" href="group__segNet.html#aadacbaf1eb15bfe512499276272bf67c">mLastInputImg</a>;        </div>
<div class="line"><a name="l00338"></a><span class="lineno"><a class="line" href="group__segNet.html#ad984bfe4460621a78440bfb4768f4e8e">  338</a></span>&#160;        uint32_t          <a class="code" href="group__segNet.html#ad984bfe4460621a78440bfb4768f4e8e">mLastInputWidth</a>;      </div>
<div class="line"><a name="l00339"></a><span class="lineno"><a class="line" href="group__segNet.html#a4341b8ae226236eef40867bab4c7f251">  339</a></span>&#160;        uint32_t          <a class="code" href="group__segNet.html#a4341b8ae226236eef40867bab4c7f251">mLastInputHeight</a>;     </div>
<div class="line"><a name="l00340"></a><span class="lineno"><a class="line" href="group__segNet.html#a2d4bf7321a21756ff82551e306e8adb1">  340</a></span>&#160;        <a class="code" href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a> <a class="code" href="group__segNet.html#a2d4bf7321a21756ff82551e306e8adb1">mLastInputFormat</a>; </div>
<div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;};</div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160; </div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160; </div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;<span class="preprocessor">#endif</span></div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160; </div>
</div><!-- fragment --></div><!-- contents -->
</div><!-- doc-content -->
<div class="ttc" id="agroup__segNet_html_a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0"><div class="ttname"><a href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">segNet::FILTER_LINEAR</a></div><div class="ttdeci">@ FILTER_LINEAR</div><div class="ttdoc">Bilinear filtering.</div><div class="ttdef"><b>Definition:</b> segNet.h:96</div></div>
<div class="ttc" id="agroup__segNet_html_a646b59503f89809fefee1c32d33307d9"><div class="ttname"><a href="group__segNet.html#a646b59503f89809fefee1c32d33307d9">segNet::Overlay</a></div><div class="ttdeci">bool Overlay(T *output, uint32_t width, uint32_t height, FilterMode filter=FILTER_LINEAR)</div><div class="ttdoc">Produce the segmentation overlay alpha blended on top of the original image.</div><div class="ttdef"><b>Definition:</b> segNet.h:229</div></div>
<div class="ttc" id="agroup__segNet_html_a167f9d7e76b2837485278bf7323b4eac"><div class="ttname"><a href="group__segNet.html#a167f9d7e76b2837485278bf7323b4eac">segNet::~segNet</a></div><div class="ttdeci">virtual ~segNet()</div><div class="ttdoc">Destroy.</div></div>
<div class="ttc" id="agroup__segNet_html_a4eabed9f0e8aa5a8ddad078ada771ad7"><div class="ttname"><a href="group__segNet.html#a4eabed9f0e8aa5a8ddad078ada771ad7">segNet::saveClassLegend</a></div><div class="ttdeci">bool saveClassLegend(const char *filename)</div></div>
<div class="ttc" id="acudaPointCloud_8h_html_a549d5369c70bd71a70798aa5b1ea4270"><div class="ttname"><a href="cudaPointCloud_8h.html#a549d5369c70bd71a70798aa5b1ea4270">color</a></div><div class="ttdeci">uchar3 color</div><div class="ttdoc">The RGB color of the point.</div><div class="ttdef"><b>Definition:</b> cudaPointCloud.h:11</div></div>
<div class="ttc" id="agroup__segNet_html_a95980d825a9939d0f48bfb2ef51ebb79"><div class="ttname"><a href="group__segNet.html#a95980d825a9939d0f48bfb2ef51ebb79">segNet::GetGridHeight</a></div><div class="ttdeci">uint32_t GetGridHeight() const</div><div class="ttdoc">Retrieve the number of rows in the classification grid.</div><div class="ttdef"><b>Definition:</b> segNet.h:316</div></div>
<div class="ttc" id="agroup__segNet_html_af480f63626ccb573caa816c9446930f5"><div class="ttname"><a href="group__segNet.html#af480f63626ccb573caa816c9446930f5">segNet::VisualizationFlagsFromStr</a></div><div class="ttdeci">static uint32_t VisualizationFlagsFromStr(const char *str, uint32_t default_value=VISUALIZE_OVERLAY)</div><div class="ttdoc">Parse a string of one of more VisualizationMode values.</div></div>
<div class="ttc" id="agroup__segNet_html_aadacbaf1eb15bfe512499276272bf67c"><div class="ttname"><a href="group__segNet.html#aadacbaf1eb15bfe512499276272bf67c">segNet::mLastInputImg</a></div><div class="ttdeci">void * mLastInputImg</div><div class="ttdoc">last input image to be processed, stored for overlay</div><div class="ttdef"><b>Definition:</b> segNet.h:337</div></div>
<div class="ttc" id="agroup__segNet_html_a895252269f201c23e8887d2774ec5ac4"><div class="ttname"><a href="group__segNet.html#a895252269f201c23e8887d2774ec5ac4">segNet::GetClassLabel</a></div><div class="ttdeci">const char * GetClassLabel(uint32_t id) const</div><div class="ttdoc">Retrieve the description of a particular class.</div><div class="ttdef"><b>Definition:</b> segNet.h:268</div></div>
<div class="ttc" id="agroup__segNet_html_a04bb46f8a71a45044d324a5e140f0777"><div class="ttname"><a href="group__segNet.html#a04bb46f8a71a45044d324a5e140f0777">segNet::FindClassID</a></div><div class="ttdeci">int FindClassID(const char *label_name)</div><div class="ttdoc">Find the ID of a particular class (by label name).</div></div>
<div class="ttc" id="agroup__segNet_html_a2d4bf7321a21756ff82551e306e8adb1"><div class="ttname"><a href="group__segNet.html#a2d4bf7321a21756ff82551e306e8adb1">segNet::mLastInputFormat</a></div><div class="ttdeci">imageFormat mLastInputFormat</div><div class="ttdoc">pixel format of last input image</div><div class="ttdef"><b>Definition:</b> segNet.h:340</div></div>
<div class="ttc" id="agroup__segNet_html_a973c337a2c3d7371c6b7cebd3aa2ade0"><div class="ttname"><a href="group__segNet.html#a973c337a2c3d7371c6b7cebd3aa2ade0">segNet::GetClassPath</a></div><div class="ttdeci">const char * GetClassPath() const</div><div class="ttdoc">Retrieve the path to the file containing the class label descriptions.</div><div class="ttdef"><b>Definition:</b> segNet.h:304</div></div>
<div class="ttc" id="agroup__segNet_html_aeb2ea51dc7597c832bcb1ae61301d678"><div class="ttname"><a href="group__segNet.html#aeb2ea51dc7597c832bcb1ae61301d678">segNet::overlayPoint</a></div><div class="ttdeci">bool overlayPoint(void *input, uint32_t in_width, uint32_t in_height, imageFormat in_format, void *output, uint32_t out_width, uint32_t out_height, imageFormat out_format, bool mask_only)</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b"><div class="ttname"><a href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a></div><div class="ttdeci">@ DEVICE_GPU</div><div class="ttdoc">GPU (if multiple GPUs are present, a specific GPU can be selected with cudaSetDevice()</div><div class="ttdef"><b>Definition:</b> tensorNet.h:131</div></div>
<div class="ttc" id="atensorNet_8h_html_a2dd230b8ba7267356e52b308b5c40077"><div class="ttname"><a href="tensorNet_8h.html#a2dd230b8ba7267356e52b308b5c40077">DIMS_C</a></div><div class="ttdeci">#define DIMS_C(x)</div><div class="ttdef"><b>Definition:</b> tensorNet.h:60</div></div>
<div class="ttc" id="agroup__segNet_html_a299e7f53cde4e3e25cd00829dc181a10"><div class="ttname"><a href="group__segNet.html#a299e7f53cde4e3e25cd00829dc181a10">segNet::FilterModeFromStr</a></div><div class="ttdeci">static FilterMode FilterModeFromStr(const char *str, FilterMode default_value=FILTER_LINEAR)</div><div class="ttdoc">Parse a string from one of the FilterMode values.</div></div>
<div class="ttc" id="agroup__segNet_html_ga33b5fd20f8ed468725c55eb0bcc5af71"><div class="ttname"><a href="group__segNet.html#ga33b5fd20f8ed468725c55eb0bcc5af71">SEGNET_DEFAULT_INPUT</a></div><div class="ttdeci">#define SEGNET_DEFAULT_INPUT</div><div class="ttdoc">Name of default input blob for segmentation model.</div><div class="ttdef"><b>Definition:</b> segNet.h:34</div></div>
<div class="ttc" id="agroup__tensorNet_html_gaa5d3f9981cdbd91516c1474006a80fe4"><div class="ttname"><a href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a></div><div class="ttdeci">deviceType</div><div class="ttdoc">Enumeration for indicating the desired device that the network should run on, if available in hardwar...</div><div class="ttdef"><b>Definition:</b> tensorNet.h:129</div></div>
<div class="ttc" id="agroup__segNet_html_a5579582306d8b98e3a8acf2b73e13ea0"><div class="ttname"><a href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0">segNet::FilterMode</a></div><div class="ttdeci">FilterMode</div><div class="ttdoc">Enumeration of mask/overlay filtering modes.</div><div class="ttdef"><b>Definition:</b> segNet.h:93</div></div>
<div class="ttc" id="agroup__segNet_html_afdf19dd9b97d89fa0074c75db4263eac"><div class="ttname"><a href="group__segNet.html#afdf19dd9b97d89fa0074c75db4263eac">segNet::GetClassColor</a></div><div class="ttdeci">float4 GetClassColor(uint32_t id) const</div><div class="ttdoc">Retrieve the RGBA visualization color a particular class.</div><div class="ttdef"><b>Definition:</b> segNet.h:278</div></div>
<div class="ttc" id="atensorNet_8h_html"><div class="ttname"><a href="tensorNet_8h.html">tensorNet.h</a></div></div>
<div class="ttc" id="agroup__segNet_html_ac93f4a93e1321260a8f0584614185305"><div class="ttname"><a href="group__segNet.html#ac93f4a93e1321260a8f0584614185305">segNet::SetClassColor</a></div><div class="ttdeci">void SetClassColor(uint32_t classIndex, const float4 &amp;color)</div><div class="ttdoc">Set the visualization color of a particular class of object.</div></div>
<div class="ttc" id="atensorNet_8h_html_a1fc0b1785ea99bd75ec83b1eeb4e6120"><div class="ttname"><a href="tensorNet_8h.html#a1fc0b1785ea99bd75ec83b1eeb4e6120">DIMS_H</a></div><div class="ttdeci">#define DIMS_H(x)</div><div class="ttdef"><b>Definition:</b> tensorNet.h:61</div></div>
<div class="ttc" id="agroup__tensorNet_html_ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9"><div class="ttname"><a href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a></div><div class="ttdeci">@ TYPE_FASTEST</div><div class="ttdoc">The fastest detected precision should be use (i.e.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:105</div></div>
<div class="ttc" id="agroup__segNet_html_ac8cbd9449fb81520a847aee04b6bbca5"><div class="ttname"><a href="group__segNet.html#ac8cbd9449fb81520a847aee04b6bbca5">segNet::mColorsAlphaSet</a></div><div class="ttdeci">bool * mColorsAlphaSet</div><div class="ttdoc">true if class color had been explicitly set from file or user</div><div class="ttdef"><b>Definition:</b> segNet.h:333</div></div>
<div class="ttc" id="agroup__segNet_html_a31d2bd6ddf05ce178a8e6c5b88247075"><div class="ttname"><a href="group__segNet.html#a31d2bd6ddf05ce178a8e6c5b88247075">segNet::loadClassLabels</a></div><div class="ttdeci">bool loadClassLabels(const char *filename)</div></div>
<div class="ttc" id="agroup__segNet_html_af5a935f07770a98dcd33d59d8e9751d1"><div class="ttname"><a href="group__segNet.html#af5a935f07770a98dcd33d59d8e9751d1">segNet::Create</a></div><div class="ttdeci">static segNet * Create(const char *network=&quot;fcn-resnet18-voc&quot;, uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, bool allowGPUFallback=true)</div><div class="ttdoc">Load a pre-trained model.</div></div>
<div class="ttc" id="agroup__segNet_html_aadc91d5c05834ab706691c4861448bc8"><div class="ttname"><a href="group__segNet.html#aadc91d5c05834ab706691c4861448bc8">segNet::overlayLinear</a></div><div class="ttdeci">bool overlayLinear(void *input, uint32_t in_width, uint32_t in_height, imageFormat in_format, void *output, uint32_t out_width, uint32_t out_height, imageFormat out_format, bool mask_only)</div></div>
<div class="ttc" id="agroup__tensorNet_html_gaac6604fd52c6e5db82877390e0378623"><div class="ttname"><a href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a></div><div class="ttdeci">precisionType</div><div class="ttdoc">Enumeration for indicating the desired precision that the network should run in, if available in hard...</div><div class="ttdef"><b>Definition:</b> tensorNet.h:102</div></div>
<div class="ttc" id="agroup__segNet_html_a04b332bd106de1f8238d34f36fb97442"><div class="ttname"><a href="group__segNet.html#a04b332bd106de1f8238d34f36fb97442">segNet::Process</a></div><div class="ttdeci">bool Process(T *input, uint32_t width, uint32_t height, const char *ignore_class=&quot;void&quot;)</div><div class="ttdoc">Perform the initial inferencing processing portion of the segmentation.</div><div class="ttdef"><b>Definition:</b> segNet.h:175</div></div>
<div class="ttc" id="agroup__segNet_html_classsegNet"><div class="ttname"><a href="group__segNet.html#classsegNet">segNet</a></div><div class="ttdoc">Image segmentation with FCN-Alexnet or custom models, using TensorRT.</div><div class="ttdef"><b>Definition:</b> segNet.h:87</div></div>
<div class="ttc" id="agroup__segNet_html_a5579582306d8b98e3a8acf2b73e13ea0abe4ae38cf99cdab6c3b070ee4a83bb47"><div class="ttname"><a href="group__segNet.html#a5579582306d8b98e3a8acf2b73e13ea0abe4ae38cf99cdab6c3b070ee4a83bb47">segNet::FILTER_POINT</a></div><div class="ttdeci">@ FILTER_POINT</div><div class="ttdoc">Nearest point sampling.</div><div class="ttdef"><b>Definition:</b> segNet.h:95</div></div>
<div class="ttc" id="agroup__segNet_html_af2a45b6307104ed74714349becc0495c"><div class="ttname"><a href="group__segNet.html#af2a45b6307104ed74714349becc0495c">segNet::segNet</a></div><div class="ttdeci">segNet()</div></div>
<div class="ttc" id="agroup__segNet_html_a09a07cb06cd461f6003b655e945d9cf3a44b13e054270ce1d9a77fea8bfa83bd5"><div class="ttname"><a href="group__segNet.html#a09a07cb06cd461f6003b655e945d9cf3a44b13e054270ce1d9a77fea8bfa83bd5">segNet::VISUALIZE_MASK</a></div><div class="ttdeci">@ VISUALIZE_MASK</div><div class="ttdoc">View just the colorized segmentation class mask.</div><div class="ttdef"><b>Definition:</b> segNet.h:105</div></div>
<div class="ttc" id="agroup__segNet_html_ga1b784139a64e71b3698a234d83ae2cf8"><div class="ttname"><a href="group__segNet.html#ga1b784139a64e71b3698a234d83ae2cf8">SEGNET_USAGE_STRING</a></div><div class="ttdeci">#define SEGNET_USAGE_STRING</div><div class="ttdoc">Standard command-line options able to be passed to segNet::Create()</div><div class="ttdef"><b>Definition:</b> segNet.h:58</div></div>
<div class="ttc" id="agroup__segNet_html_a3db3738778929458b52a709b053d456a"><div class="ttname"><a href="group__segNet.html#a3db3738778929458b52a709b053d456a">segNet::mClassMap</a></div><div class="ttdeci">uint8_t * mClassMap</div><div class="ttdoc">runtime buffer for the argmax-classified class index of each tile</div><div class="ttdef"><b>Definition:</b> segNet.h:335</div></div>
<div class="ttc" id="agroup__tensorNet_html_classtensorNet"><div class="ttname"><a href="group__tensorNet.html#classtensorNet">tensorNet</a></div><div class="ttdoc">Abstract class for loading a tensor network with TensorRT.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:218</div></div>
<div class="ttc" id="agroup__segNet_html_af7b6257716514631dd0358e4b2ed692c"><div class="ttname"><a href="group__segNet.html#af7b6257716514631dd0358e4b2ed692c">segNet::Mask</a></div><div class="ttdeci">bool Mask(T *output, uint32_t width, uint32_t height, FilterMode filter=FILTER_LINEAR)</div><div class="ttdoc">Produce a colorized segmentation mask.</div><div class="ttdef"><b>Definition:</b> segNet.h:201</div></div>
<div class="ttc" id="agroup__segNet_html_aa4c64609fb07586bed32ac4b8e9058d7"><div class="ttname"><a href="group__segNet.html#aa4c64609fb07586bed32ac4b8e9058d7">segNet::SetOverlayAlpha</a></div><div class="ttdeci">void SetOverlayAlpha(float alpha, bool explicit_exempt=true)</div><div class="ttdoc">Set overlay alpha blending value for all classes (between 0-255), (optionally except for those that h...</div></div>
<div class="ttc" id="agroup__segNet_html_a27a03d12169f62dac97e351b2acdea86"><div class="ttname"><a href="group__segNet.html#a27a03d12169f62dac97e351b2acdea86">segNet::GetOverlayAlpha</a></div><div class="ttdeci">float GetOverlayAlpha() const</div><div class="ttdoc">Retrieve the overlay alpha blending value for classes that don't have it explicitly set.</div></div>
<div class="ttc" id="atensorNet_8h_html_a7d959cb65990da8bfea3d941d6daf416"><div class="ttname"><a href="tensorNet_8h.html#a7d959cb65990da8bfea3d941d6daf416">DIMS_W</a></div><div class="ttdeci">#define DIMS_W(x)</div><div class="ttdef"><b>Definition:</b> tensorNet.h:62</div></div>
<div class="ttc" id="agroup__segNet_html_ga05c359c7dcd0c1e855543a3a9a18c422"><div class="ttname"><a href="group__segNet.html#ga05c359c7dcd0c1e855543a3a9a18c422">SEGNET_DEFAULT_OUTPUT</a></div><div class="ttdeci">#define SEGNET_DEFAULT_OUTPUT</div><div class="ttdoc">Name of default output blob for segmentation model.</div><div class="ttdef"><b>Definition:</b> segNet.h:40</div></div>
<div class="ttc" id="agroup__segNet_html_a09a07cb06cd461f6003b655e945d9cf3"><div class="ttname"><a href="group__segNet.html#a09a07cb06cd461f6003b655e945d9cf3">segNet::VisualizationFlags</a></div><div class="ttdeci">VisualizationFlags</div><div class="ttdoc">Visualization flags.</div><div class="ttdef"><b>Definition:</b> segNet.h:102</div></div>
<div class="ttc" id="agroup__segNet_html_a0e11d4bd854120f1709c306e91e44389"><div class="ttname"><a href="group__segNet.html#a0e11d4bd854120f1709c306e91e44389">segNet::Usage</a></div><div class="ttdeci">static const char * Usage()</div><div class="ttdoc">Usage string for command line arguments to Create()</div><div class="ttdef"><b>Definition:</b> segNet.h:160</div></div>
<div class="ttc" id="agroup__segNet_html_a5763fca156e99d9fe07dcbf626489b0e"><div class="ttname"><a href="group__segNet.html#a5763fca156e99d9fe07dcbf626489b0e">segNet::mClassLabels</a></div><div class="ttdeci">std::vector&lt; std::string &gt; mClassLabels</div><div class="ttdef"><b>Definition:</b> segNet.h:330</div></div>
<div class="ttc" id="agroup__segNet_html_af35b6253e85cfe6c30ac0a1a7ca3fcc8"><div class="ttname"><a href="group__segNet.html#af35b6253e85cfe6c30ac0a1a7ca3fcc8">segNet::GetClassDesc</a></div><div class="ttdeci">const char * GetClassDesc(uint32_t id) const</div><div class="ttdoc">Retrieve the description of a particular class.</div><div class="ttdef"><b>Definition:</b> segNet.h:273</div></div>
<div class="ttc" id="agroup__segNet_html_a96b6fe6b05534c0792f8cc9353723219"><div class="ttname"><a href="group__segNet.html#a96b6fe6b05534c0792f8cc9353723219">segNet::GetGridWidth</a></div><div class="ttdeci">uint32_t GetGridWidth() const</div><div class="ttdoc">Retrieve the number of columns in the classification grid.</div><div class="ttdef"><b>Definition:</b> segNet.h:310</div></div>
<div class="ttc" id="agroup__segNet_html_a307dd9f1d322ce42f553361321bbb869"><div class="ttname"><a href="group__segNet.html#a307dd9f1d322ce42f553361321bbb869">segNet::mClassColors</a></div><div class="ttdeci">float4 * mClassColors</div><div class="ttdoc">array of overlay colors in shared CPU/GPU memory</div><div class="ttdef"><b>Definition:</b> segNet.h:334</div></div>
<div class="ttc" id="agroup__segNet_html_a09a07cb06cd461f6003b655e945d9cf3ab6a2dc917492d6b83de4b94c9233cb5f"><div class="ttname"><a href="group__segNet.html#a09a07cb06cd461f6003b655e945d9cf3ab6a2dc917492d6b83de4b94c9233cb5f">segNet::VISUALIZE_OVERLAY</a></div><div class="ttdeci">@ VISUALIZE_OVERLAY</div><div class="ttdoc">Overlay the segmentation class colors with alpha blending.</div><div class="ttdef"><b>Definition:</b> segNet.h:104</div></div>
<div class="ttc" id="agroup__segNet_html_ad984bfe4460621a78440bfb4768f4e8e"><div class="ttname"><a href="group__segNet.html#ad984bfe4460621a78440bfb4768f4e8e">segNet::mLastInputWidth</a></div><div class="ttdeci">uint32_t mLastInputWidth</div><div class="ttdoc">width in pixels of last input image to be processed</div><div class="ttdef"><b>Definition:</b> segNet.h:338</div></div>
<div class="ttc" id="agroup__tensorNet_html_ga5a46a965749d6118e01307fd4d4865c9"><div class="ttname"><a href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a></div><div class="ttdeci">#define DEFAULT_MAX_BATCH_SIZE</div><div class="ttdoc">Default maximum batch size.</div><div class="ttdef"><b>Definition:</b> tensorNet.h:88</div></div>
<div class="ttc" id="agroup__segNet_html_a3b98b9827d5c07e84ed6711414b96554"><div class="ttname"><a href="group__segNet.html#a3b98b9827d5c07e84ed6711414b96554">segNet::classify</a></div><div class="ttdeci">bool classify(const char *ignore_class)</div></div>
<div class="ttc" id="agroup__segNet_html_a4341b8ae226236eef40867bab4c7f251"><div class="ttname"><a href="group__segNet.html#a4341b8ae226236eef40867bab4c7f251">segNet::mLastInputHeight</a></div><div class="ttdeci">uint32_t mLastInputHeight</div><div class="ttdoc">height in pixels of last input image to be processed</div><div class="ttdef"><b>Definition:</b> segNet.h:339</div></div>
<div class="ttc" id="agroup__commandLine_html_classcommandLine"><div class="ttname"><a href="group__commandLine.html#classcommandLine">commandLine</a></div><div class="ttdoc">Command line parser for extracting flags, values, and strings.</div><div class="ttdef"><b>Definition:</b> commandLine.h:35</div></div>
<div class="ttc" id="agroup__segNet_html_a218a2c71cb4d59476070385c7370f789"><div class="ttname"><a href="group__segNet.html#a218a2c71cb4d59476070385c7370f789">segNet::loadClassColors</a></div><div class="ttdeci">bool loadClassColors(const char *filename)</div></div>
<div class="ttc" id="agroup__imageFormat_html_ga931c48e08f361637d093355d64583406"><div class="ttname"><a href="group__imageFormat.html#ga931c48e08f361637d093355d64583406">imageFormat</a></div><div class="ttdeci">imageFormat</div><div class="ttdoc">The imageFormat enum is used to identify the pixel format and colorspace of an image.</div><div class="ttdef"><b>Definition:</b> imageFormat.h:49</div></div>
<div class="ttc" id="agroup__segNet_html_af9a9bd73dc17940aa87aacba2001b09b"><div class="ttname"><a href="group__segNet.html#af9a9bd73dc17940aa87aacba2001b09b">segNet::mClassPath</a></div><div class="ttdeci">std::string mClassPath</div><div class="ttdef"><b>Definition:</b> segNet.h:331</div></div>
<div class="ttc" id="agroup__segNet_html_a31e8118b2a38e330b6e087cf6c98396e"><div class="ttname"><a href="group__segNet.html#a31e8118b2a38e330b6e087cf6c98396e">segNet::GetNumClasses</a></div><div class="ttdeci">uint32_t GetNumClasses() const</div><div class="ttdoc">Retrieve the number of object classes supported in the detector.</div><div class="ttdef"><b>Definition:</b> segNet.h:263</div></div>
<div class="ttc" id="agroup__tensorNet_html_afcdbdb26dc6e5117f867c83e635a0250"><div class="ttname"><a href="group__tensorNet.html#afcdbdb26dc6e5117f867c83e635a0250">tensorNet::mOutputs</a></div><div class="ttdeci">std::vector&lt; layerInfo &gt; mOutputs</div><div class="ttdef"><b>Definition:</b> tensorNet.h:819</div></div>
<div class="ttc" id="acudaVector_8h_html_aa94774faf063d34dab6f3f374d73ea7a"><div class="ttname"><a href="cudaVector_8h.html#aa94774faf063d34dab6f3f374d73ea7a">alpha</a></div><div class="ttdeci">__device__ cudaVectorTypeInfo&lt; T &gt;::Base alpha(T vec, typename cudaVectorTypeInfo&lt; T &gt;::Base default_alpha=255)</div><div class="ttdef"><b>Definition:</b> cudaVector.h:98</div></div>
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